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Ioannis Ganoulis

24 June 2024
STATISTICS PAPER SERIES - No. 47
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Abstract
The Harmonised Index of Consumer Prices (HICP) currently only includes rentals for housing (paid by tenants) and auxiliary housing expenditures (paid by both tenants and owners). The inclusion of an item for owner-occupied housing (OOH) would be desirable for both representativeness and cross-country comparability. This paper reviews the potential options for including OOH in the HICP to derive a new inflation index. We discuss the conceptual and measurement issues involved. Additionally, we present our analytical calculations on the impact and economic properties of this index as compared to the HICP. We show that since 2011 the estimated impact of including OOH in HICP annual inflation, based on either the “net acquisition” approach or the “rental equivalence” approach, would have been within a band of between -1.2 and +0.4 percentage points. The net acquisition approach could result in bigger differences in future, should the fluctuations in the housing market cycles in the euro area be more pronounced and synchronised. The results should be interpreted keeping in mind that the period of observation is relatively short in relation to housing market cycles. In general, the empirical evidence suggests that including OOH based on the rental equivalence approach decreases the cyclicality of the new inflation index, while the net acquisition approach implies a small amplification of its cyclical properties compared to the HICP.
JEL Code
C43 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Index Numbers and Aggregation
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
21 September 2021
OCCASIONAL PAPER SERIES - No. 265
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Abstract
This paper – which takes into consideration overall experience with the Harmonised Index of Consumer Prices (HICP) as well as the improvements made to this measure of inflation since 2003 – finds that the HICP continues to fulfil the prerequisites for the index underlying the ECB’s definition of price stability. Nonetheless, there is scope for enhancing the HICP, especially by including owner-occupied housing (OOH) using the net acquisitions approach. Filling this long-standing gap is of utmost importance to increase the coverage and cross-country comparability of the HICP. In addition to integrating OOH into the HICP, further improvements would be welcome in harmonisation, especially regarding the treatment of product replacement and quality adjustment. Such measures may also help reduce the measurement bias that still exists in the HICP. Overall, a knowledge gap concerning the exact size of the measurement bias of the HICP remains, which calls for further research. More generally, the paper also finds that auxiliary inflation measures can play an important role in the ECB’s economic and monetary analyses. This applies not only to analytical series including OOH, but also to measures of underlying inflation or a cost of living index.
JEL Code
C43 : Mathematical and Quantitative Methods→Econometric and Statistical Methods: Special Topics→Index Numbers and Aggregation
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
C82 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Macroeconomic Data, Data Access
E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
20 July 2020
WORKING PAPER SERIES - No. 2446
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Abstract
This paper provides novel information on the propagation of the pandemic-induced real shock to firms’ financial conditions. It uses firm-level survey data from end February to early April 2020 for a large sample of euro area SMEs and large firms. Firms’ expectations on the availability of credit lines, bank loans and trade credit deteriorated significantly in the first half of March. Firms mostly expected to be affected if they had previously difficulties in securing finance, had higher indebtedness and, hence, less capacity to deal with a liquidity shock. Conditional on these factors, firm size does not seem to matter, except for trade credit, in which case SMEs had more positive conditional expectations. Together with the overall deterioration of expectations, there seems to have also been a reallocation of opportunities to access finance amidst the crisis. Small firms were more likely to have conditional expectations of improvement in their access to finance.
JEL Code
C83 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Survey Methods, Sampling Methods
D22 : Microeconomics→Production and Organizations→Firm Behavior: Empirical Analysis
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
E65 : Macroeconomics and Monetary Economics→Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook→Studies of Particular Policy Episodes
L25 : Industrial Organization→Firm Objectives, Organization, and Behavior→Firm Performance: Size, Diversification, and Scope
16 December 2019
WORKING PAPER SERIES - No. 2341
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Abstract
Using a large set of firm-level survey data from the euro area since 2009, we analyse how firms use their information to form expectations on the availability of bank finance. Our results suggest that firms update what otherwise look like adaptive expectations on the basis of the latest information in their information set. As in the previous literature, the hypothesis that expectations fulfil the (orthogonality) conditions of the rational expectations hypothesis is rejected by the data. We find evidence that this is not only due to information imperfections but also to some type of misspecification of the expectations’ model that firms are using. In addition, we find some evidence that companies that have not used bank finance recently tend to do worse at forecasting its availability next period. To test how policy announcements may affect expectations, we concentrate on the possible effects of the ECB policy announcements of summer 2012, which included among other things the announcement of the European Central Bank’s Outright Monetary Transactions Program (OMT). Using a difference-in-differences approach, we find evidence of forward-looking expectations. In particular, shortly after the OMT announcement the forecast of “informed” firms were more upbeat compared to the control group of firms. This moreover was true in both vulnerable and non-vulnerable countries, suggesting that it was the relevance of the information about the future of the banking system that most mattered for expectations at the time, more than the immediate impact of the announced policy measures.
JEL Code
C83 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Survey Methods, Sampling Methods
D22 : Microeconomics→Production and Organizations→Firm Behavior: Empirical Analysis
D84 : Microeconomics→Information, Knowledge, and Uncertainty→Expectations, Speculations
17 May 2019
OCCASIONAL PAPER SERIES - No. 223
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Abstract
This paper summarises the outcomes of the analysis of the ECB Crypto-Assets Task Force. First, it proposes a characterisation of crypto-assets in the absence of a common definition and as a basis for the consistent analysis of this phenomenon. Second, it analyses recent developments in the crypto-assets market and unfolding links with financial markets and the economy. Finally, it assesses the potential impact of crypto-assets on monetary policy, payments and market infrastructures, and financial stability. The analysis shows that, in the current market, crypto-assets’ risks or potential implications are limited and/or manageable on the basis of the existing regulatory and oversight frameworks. However, this assessment is subject to change and should not prevent the ECB from continuing to monitor crypto-assets, raise awareness and develop preparedness.
JEL Code
E42 : Macroeconomics and Monetary Economics→Money and Interest Rates→Monetary Systems, Standards, Regimes, Government and the Monetary System, Payment Systems
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G23 : Financial Economics→Financial Institutions and Services→Non-bank Financial Institutions, Financial Instruments, Institutional Investors
O33 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights→Technological Change: Choices and Consequences, Diffusion Processes
21 August 2012
WORKING PAPER SERIES - No. 1461
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Abstract
In comparison with the large literature on house prices, housing investments have been studied far less. This paper investigates the behaviour of private residential investments for the six largest European economies, namely: Germany, France, Italy, Spain, the Netherlands and the United Kingdom. It employs a common modelling structure based on an error correction approach and country specific models. First, co-integration among the parsimoniously specified set of fundamental variables is detected in all countries. Second, cross-country differences are found in the responsiveness of private residential investments to real prices and to other relevant factors. Germany has the strongest response of private residential investments to house price changes whereas Italy shows the lowest responses. In Spain investments seem to be primarily related to their lagged component and short-term changes in house prices, and show a poor relationship with deviations from long-term fundamentals. In some countries, the lagged component of residential investments seems to point to a high persistency effect.
JEL Code
C2 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables
R30 : Urban, Rural, Regional, Real Estate, and Transportation Economics→Real Estate Markets, Spatial Production Analysis, and Firm Location→General
E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity